Skill UI

This skill is designed for Heads of Procurement or BizOps leaders conducting annual category reviews. It analyzes complex enterprise spending patterns by categorizing costs using UNSPSC standards, identifying the top cost drivers (Pareto analysis), and diagnosing bottlenecks in the purchasing cycle. It generates a defensible, risk-balanced plan for supplier consolidation, ensuring no critical tier-1 category is collapsed to a single source without documented contingency plans.

This skill provides a comprehensive audit of GitHub Actions workflows. It inspects CI configurations to identify bottlenecks, waste sources, and areas for optimization, helping users reduce runtime, lower costs, and boost overall CI/CD efficiency. It covers caching, concurrency, and trigger reduction.

This workflow systematically analyzes deployed AWS resources and Infrastructure-as-Code (IaC) definitions. It collects usage metrics from CloudWatch and Cost Explorer to identify over-provisioning, unused resources, and inefficient configurations (e.g., right-sizing EC2, S3 lifecycle policies). It generates actionable cost optimization recommendations and creates structured GitHub issues for tracking and implementing savings.

A comprehensive skill for managing AWS operational excellence, cost governance, and observability. It provides guidance on pre-deployment cost estimation (TCO), detailed spending analysis using Cost Explorer, setup of CloudWatch alarms, auditing activity via CloudTrail, and overall security posture assessment. Essential for optimizing cloud spending and ensuring reliable infrastructure.

A rigorous, data-driven methodology for improving system performance. Use this skill when aiming to significantly increase speed, reduce latency, or lower operational cost. It establishes a measurable baseline, generates testable variants based on hypotheses, runs controlled benchmarks, and validates the best performing solution through iterative testing and code promotion gates.

A comprehensive pattern for building robust and cost-efficient LLM application pipelines. This guide details combining model routing based on task complexity, immutable cost tracking, limited retry logic, and prompt caching to manage API expenditures while maintaining high quality. Essential for production systems handling variable-complexity, high-volume tasks.

This tool wraps the hooks routing mechanism to classify tasks into tiers based on Agent Booster eligibility. It calculates potential cost savings by identifying Tier 1 bypass tasks (which cost $0) versus standard LLM calls. It is essential for optimizing large batches of simple, predictable operations and reporting accurate resource utilization.

This skill analyzes historical token usage across AI agents and models to pinpoint areas of inefficiency and waste. It recommends specific optimizations—such as model tier adjustments, improving cache utilization, or removing redundant agents—providing estimated dollar savings and actionable steps to reduce operational costs.

A comprehensive expert system simulating 15+ years of experience in global trade compliance (US, EU, UK, APAC). It specializes in HS/HTS classification, tariff optimization, sanctioned party screening (SDN), and preparing complex customs documentation to ensure legal, cost-effective, and compliant cross-border goods movement.

A comprehensive resource providing codified expertise for managing complex energy portfolios for large commercial and industrial (C&I) consumers. Covers electricity and gas procurement, tariff structure analysis (TOU, RTP), demand charge mitigation, PPA evaluation, and multi-site energy strategy development. Ideal for optimizing utility spending, understanding complex utility bills, and building resilient, sustainable energy supply chains.

This tool executes a GEPA learning cycle, automating the evolution and optimization of policy prompts against a scored task corpus. Instead of relying on manual prompt iteration, it measures performance improvements, identifying the best working 'harness genome.' It is ideal for measuring sustainable improvements in task performance and supports a free, cost-estimating dry-run mode before committing to actual model calls.